↓ 7 callersMethod__init__(self, *, ch, out_ch, ch_mult=(1, 2, 4, 8), num_res_blocks, attn_resolutions, dropout=0.0, resamp_with_conv=Tr
backend/nn/vae.py:141
↓ 7 callersMethod__init__(self, channels=[320, 640, 1280, 1280], nums_rb=3, cin=64, ksize=3, sk=False, use_conv=True, xl=True)
backend/nn/cnets/t2i_adapter.py:104
↓ 7 callersMethodrun Run one decode step. input_embeds: [1, 1, hidden_size] position: current sequence position Returns: [1, 1, hidden_siz
extensions-builtin/forge_space_Qwen3_TTS/huggingface_space_mirror/faster_qwen3_tts/talker_graph.py:199
↓ 6 callersMethod__init__(self, in_channels, out_channels, kernel_size,
ratio_gin, ratio_gout, stride=1, padding=0,
extensions-builtin/forge_preprocessor_inpaint/annotator/FFCResNet.py:175
↓ 6 callersMethod__init__(self, sigma_data=1.0, prediction_type='epsilon', beta_schedule='linear', linear_start=0.00085,
backend/modules/k_prediction.py:113
↓ 6 callersFunction_gen_efficientnet_edge(variant, channel_multiplier=1.0, depth_multiplier=1.0, pretrained=False, **kwargs)
extensions-builtin/forge_preprocessor_normalbae/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/gen_efficientnet.py:548
↓ 6 callersFunctiontiled_scale(samples, function, tile=(64, 64), overlap=8, upscale_amount=4, out_channels=3, output_device="cpu")
backend/patcher/vae.py:10
↓ 5 callersMethod__init__(self, in_chs, out_chs, kernel_size,
stride=1, pad_type='', act_layer=nn.ReLU, norm_layer=nn.
extensions-builtin/forge_preprocessor_normalbae/annotator/normalbae/models/submodules/efficientnet_repo/geffnet/efficientnet_builder.py:123
↓ 5 callersMethod_wrap_fn(cls, fn: Callable, *, use_self: LazyBase | None = None, meta_noop: bool | DTypeLike | tuple[DTypeLike, Callab
packages/gguf/lazy.py:110
↓ 5 callersFunctionadd_optional_chunk_mask Apply optional mask for encoder. Args: xs (torch.Tensor): padded input, (B, L, D), L for max length mask (torch.Tensor): mask fo
extensions-builtin/forge_space_ChatterboxTurbo/huggingface_space_mirror/chatterbox/models/s3gen/utils/mask.py:89
↓ 5 callersMethodapply_model(self, x, t, c_concat=None, c_crossattn=None, control=None, transformer_options={}, **kwargs)
backend/modules/k_model.py:27